| Description |
1 online resource |
| Series |
For dummies |
|
--For dummies.
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| Summary |
Big data figures into everything from weather forecasting to political polling. You'll get a handle on the statistical methods used when working with big data, applications for it, ways to organize and check data, and a whole lot more. You will find out what big data is, characteristics that define it, how it's used, and what it makes possible; how to handle it by exploring statistical techniques used with big data, including probability distributions, regression analysis, time series analysis, and forecasting techniques; learn how big data can be analyzed with graphical techniques and how to identify valid, useful, and understandable patterns in data; examine key univariate and multivariate statistical techniques for analyzing data; discover techniques for forecasting the future values of a dataset; learn about the best software packages and programming tools for analyzing statistical data. -- Edited summary from book. |
| Contents |
Title Page; Copyright Page; Table of Contents; Introduction; About This Book; Foolish Assumptions; Icons Used in This Book; Beyond the Book; Where to Go From Here; Part I Introducing Big Data Statistics; Chapter 1 What Is Big Data and What Do You Do with It?; Characteristics of Big Data; Exploratory Data Analysis (EDA); Graphical EDA techniques; Quantitative EDA techniques; Statistical Analysis of Big Data; Probability distributions; Regression analysis; Time series analysis; Forecasting techniques; Chapter 2 Characteristics of Big Data: The Three Vs; Characteristics of Big Data; Volume. |
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VelocityVariety; Traditional Database Management Systems (DBMS); Relational model databases; Hierarchical model databases; Network model databases; Alternatives to traditional database systems; Chapter 3 Using Big Data: The Hot Applications; Big Data and Weather Forecasting; Big Data and Healthcare Services; Big Data and Insurance; Big Data and Finance; Big Data and Electric Utilities; Big Data and Higher Education; Big Data and Retailers; Nordstrom; Walmart; Amazon.com; Big Data and Search Engines; Big Data and Social Media; Chapter 4 Understanding Probabilities. |
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The Core Structure: Probability SpacesDiscrete Probability Distributions; Counting outcomes; When only two things can happen: The binomial distribution; Continuous Probability Distributions; The normal distribution; Introducing Multivariate Probability Distributions; Joint probabilities; Unconditional probabilities; Conditional probabilities; Chapter 5 Basic Statistical Ideas; Some Preliminaries Regarding Data; Nominal data; Ordinal data; Summary Statistical Measures; Measures of central tendency; Measures of dispersion; Overview of Hypothesis Testing; The null hypothesis. |
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The alternative hypothesisThe level of significance; The test statistic; The critical value (s); To reject or not to reject, that is the question; Measures of association; Higher-Order Measures; Skewness; Kurtosis; Part II Preparing and Cleaning Data; Chapter 6 Dirty Work: Preparing Your Data for Analysis; Passing the Eye Test: Does Your Data Look Correct?; Checking your sources; Verifying formats; Typecasting your data; Being Careful with Dates; Dealing with datetime formats; Taking geography into account; How your software thinks about dates; Does the Data Make Sense? |
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Checking discrete dataChecking continuous data; Frequently Encountered Data Headaches; Missing values; Duplicate records; Other Common Data Transformations; Percentiles; Standard scores; Dummy variables; Chapter 7 Figuring the Format: Important Computer File Formats; Spreadsheet Formats; Comma-separated variables (.csv); Text; Microsoft Excel; Web formats; Database Formats; Microsoft Access (.accdb); MySQL (.frm); Chapter 8 Checking Assumptions: Testing for Normality; Goodness of fit test; The chi-square distribution; The null and alternative hypotheses; The level of significance. |
| Bibliography |
Includes bibliographical references and index. |
| Subject |
Big data -- Statistical methods.
|
|
Données volumineuses -- Méthodes statistiques. |
| Added Author |
Semmelroth, David, author.
|
| Other Form: |
Print version: Anderson, Alan (Professor of economics). Statistics for big data for dummies. Hoboken, New Jersey : John Wiley & Sons, [2015] 9781118940013 (OCoLC)885229333 |
| ISBN |
9781118940037 (electronic bk.) |
|
1118940032 (electronic bk.) |
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9781118940020 (electronic bk.) |
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1118940024 (electronic bk.) |
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1118940016 (pbk. ; alk. paper) |
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9781118940013 (pbk. ; alk. paper) |
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